Intervention effects in the transmission of COVID-19 depending on the detection rate and extent of isolation

• 발행기관: 한국역학회
• 저자명: Okyu Kwon Woo-Sik Son Jin Yong Kim Jong-Hun Kim
• 간행물 정보: 『Epidemiology and Health』42, 1~7쪽, 전체 7쪽
• 주제분류: 의약학 > 면역학
• 파일형태: PDF
• 발행일자: 2020.01.01

영문 초록

OBJECTIVES: In 2020, the coronavirus disease 2019 (COVID-19) respiratory infection is spreading in Korea. In order to prevent the spread of an infectious disease, infected people must be quickly identified and isolated, and contact with the infected must be blocked early. This study attempted to verify the intervention effects on the spread of an infectious disease by using these measures in a mathematical model. METHODS: We used the susceptible-infectious-recovery (SIR) model for a virtual population group connected by a special structured network. In the model, the infected state (I) was divided into I in which the infection is undetected and Ix in which the infection is detected. The probability of transitioning from an I state to Ix can be viewed as the rate at which an infected person is found. We assumed that only those connected to each other in the network can cause infection. In addition, this study attempted to evaluate the effects of isolation by temporarily removing the connection among these people. RESULTS: In Scenario 1, only the infected are isolated; in Scenario 2, those who are connected to an infected person and are also found to be infected are isolated as well. In Scenario 3, everyone connected to an infected person are isolated. In Scenario 3, it was possible to effectively suppress the infectious disease even with a relatively slow rate of diagnosis and relatively high infection rate. CONCLUSIONS: During the epidemic, quick identification of the infected is helpful. In addition, it was possible to quantitatively show through a simulation evaluation that the management of infected individuals as well as those who are connected greatly helped to suppress the spread of infectious diseases.

목차

INTRODUCTION

MATERIALS AND METHODS

RESULTS

DISCUSSION

SUPPLEMENTARY MATERIALS

CONFLICT OF INTEREST

FUNDING

ACKNOWLEDGEMENTS

AUTHOR CONTRIBUTIONS

ORCID

REFERENCES

키워드

COVID-19 Agent-based model Non-pharmaceutical intervention Social network Isolation